Metrics of High Cofluctuation and Entropy to Describe Control of Cardiac Function in the Stellate Ganglion

Abstract

AbstractNeural control of the heart involves dynamic adaptation of mechanical and electrical indices to meet blood flow demands. The control system receives centrally-derived inputs to coordinate cardiac function on a beat-by-beat basis, producing “functional” outputs such as the blood pressure waveform. Bilateral stellate ganglia (SG) are responsible for integration of multiple inputs and efferent cardiopulmonary sympathetic neurotransmission. In this work, we investigate network processing of cardiopulmonary transduction by SG neuronal populations in porcine with chronic pacing-induced heart failure and control subjects. We derive novel metrics to describe control of cardiac function by the SG during baseline and stressed states from in vivo extracellular microelectrode recordings. Network-level spatiotemporal dynamic signatures are found by quantifying state changes in coactive neuronal populations (i.e., cofluctuations). Differences in “neural specificity” of SG network activity to specific phases of the cardiac cycle are studied using entropy estimation. Fundamental differences in information processing and cardiac control are evident in chronic heart failure where the SG exhibits: i) short-lived, high amplitude cofluctuations in baseline states, ii) greater variation in neural specificity to cardiac cycles, iii) limited sympathetic reserve during stressed states, and iv) neural network activity and cardiac control linkage that depends on disease state and cofluctuation magnitude. These findings indicate that spatiotemporal dynamics of stellate ganglion neuronal populations are altered in heart failure, and lay the groundwork for understanding dysfunction neuronal signaling reflective of cardiac sympathoexcitation.